Search results for "Intrinsics"
showing 5 items of 5 documents
Bit-Parallel Approximate Pattern Matching on the Xeon Phi Coprocessor
2014
Bit-parallel pattern matching encodes calculated values in bit arrays. This approach gains its efficiency by performing multiple updates within a machine word. An important parameter is therefore the machine word size (e.g. 32 or 64 bits). With the increasing length of vector registers, the efficient mapping of bit-parallel pattern matching algorithms onto modern high performance computing architectures is becoming increasingly important. In this paper, we investigate an efficient implementation of the Wu-Manber approximate pattern matching algorithm on the Intel Xeon Phi coprocessor. This architecture features a 512-bit long vector processing unit (VPU) as well as a large number of process…
SWAPHI-LS: Smith-Waterman Algorithm on Xeon Phi coprocessors for Long DNA Sequences
2014
As an optimal method for sequence alignment, the Smith-Waterman (SW) algorithm is widely used. Unfortunately, this algorithm is computationally demanding, especially for long sequences. This has motivated the investigation of its acceleration on a variety of high-performance computing platforms. However, most work in the literature is only suitable for short sequences. In this paper, we present SWAPHI-LS, the first parallel SW algorithm exploiting emerging Xeon Phi coprocessors to accelerate the alignment of long DNA sequences. In SWAPHI-LS, we have investigated three parallelization approaches (naive, tiled, and distributed) in order to deeply explore the inherent parallelism within Xeon P…
Pairwise DNA Sequence Alignment Optimization
2015
This chapter presents a parallel implementation of the Smith-Waterman algorithm to accelerate the pairwise alignment of DNA sequences. This algorithm is especially computationally demanding for long DNA sequences. Parallelization approaches are examined in order to deeply explore the inherent parallelism within Intel Xeon Phi coprocessors. This chapter looks at exploiting instruction-level parallelism within 512-bit single instruction multiple data instructions (vectorization) as well as thread-level parallelism over the many cores (multithreading using OpenMP). Between coprocessors, device-level parallelism through the compute power of clusters including Intel Xeon Phi coprocessors using M…
Accelerating large-scale biological database search on Xeon Phi-based neo-heterogeneous architectures
2015
In this paper we present new parallelization techniques for searching large-scale biological sequence databases with the Smith-Waterman algorithm on Xeon Phi-based neoheterogenous architectures. In order to make full use of the compute power of both the multi-core CPU and the many-core Xeon Phi hardware, we use a collaborative computing scheme as well as hybrid parallelism. At the CPU side, we employ SSE intrinsics and multi-threading to implement SIMD parallelism. At the Xeon Phi side, we use Knights Corner vector instructions to gain more data parallelism. We have presented two dynamic task distribution schemes (thread level and device level) in order to achieve better load balancing. Fur…
SWAPHI: Smith-Waterman Protein Database Search on Xeon Phi Coprocessors
2014
The maximal sensitivity of the Smith-Waterman (SW) algorithm has enabled its wide use in biological sequence database search. Unfortunately, the high sensitivity comes at the expense of quadratic time complexity, which makes the algorithm computationally demanding for big databases. In this paper, we present SWAPHI, the first parallelized algorithm employing Xeon Phi coprocessors to accelerate SW protein database search. SWAPHI is designed based on the scale-and-vectorize approach, i.e. it boosts alignment speed by effectively utilizing both the coarse-grained parallelism from the many co-processing cores (scale) and the fine-grained parallelism from the 512-bit wide single instruction, mul…